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Data are provided for more than 80 minerals and materials, along with a presentation of survey methods, summary statistics for domestic nonfuel minerals, and trends in mining and quarrying in the metals and industrial minerals industry in the United States.Virtually all metallic and industrial mineral commodities important to the U.S. economy are discussed. Background information enables analysis of the data, and covers production, consumption, prices, foreign trade, a world review, and an overall outlook.
State chapters from this publication are designed to provide statistical data and information for mineral commodities on a State-by-State basis. Additional chapters include a statistical summary and survey methods for nonfuel minerals. Audience: Geologists, trade persons working with, and buying, metals and minerals, economists, and members of the general public with an interest in the most accurate information about metals and minerals statistics in different states will want to get this official government publication from the Minerals Yearbook series. Related products: Other printed volumes in the Minerals Yearbook series can be found here: https: //bookstore.gpo.gov/catalog/science-technology/minerals-metals/minerals-yearbook Minerals and Metals resources collection is available here: https: //bookstore.gpo.gov/catalog/science-technology/minerals-metals Mining & Drilling collection is available here: https: //bookstore.gpo.gov/catalog/science-technology/mining-drilling "
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations. Table of Contents: Markov Decision Processes / Value Prediction Problems / Control / For Further Exploration
This book covers the most recent scientific and technological developments (state-of-the-art) in the field of chemical oxidation processes applicable for the efficient treatment of biologically-difficult-to-degrade, toxic and/or recalcitrant effluents originating from different manufacturing processes. It is a comprehensive review of process and pollution profiles as well as conventional, advanced and emerging treatment processes & technologies developed for the most relevant and pollution (wet processing)-intensive industrial sectors. It addresses chemical/photochemical oxidative treatment processes, case-specific treatability problems of major industrial sectors, emerging (novel) as well as pilot/full-scale applications, process integration, treatment system design & sizing criteria (figure-of-merits), cost evaluation and success stories in the application of chemical oxidative treatment processes. Chemical Oxidation Applications for Industrial Wastewaters is an essential reference for lecturers, researchers, industrial and environmental engineers and practitioners working in the field of environmental science and engineering. Visit the IWA WaterWiki to read and share material related to this title: http://www.iwawaterwiki.org/xwiki/bin/view/Articles/CHEMICALOXIDATIONAPPLICATIONSFORINDUSTRIALWASTEWATERS Authors: Professor Olcay Tünay, Professor Isik Kabdasli, Associate Professor Idil Arslan-Alaton and Assistant Professor Tugba Ölmez-Hanci, Environmental Engineering Department, Istanbul Technical University, Turkey.
Publisher Description
This book presents selected peer reviewed papers from the International Conference on Advanced Production and Industrial Engineering (ICAPIE 2019). It covers a wide range of topics and latest research in mechanical systems engineering, materials engineering, micro-machining, renewable energy, industrial and production engineering, and additive manufacturing. Given the range of topics discussed, this book will be useful for students and researchers primarily working in mechanical and industrial engineering, and energy technologies.